1. ATLAS Trigger Development
Corrinne Mills
Harvard DOE Review
August 14-15, 2008

2. The ATLAS Trigger System
Level One
hardware: calo + muon
(75 kHz)
triggers
Level Two
software: partial reco.
(3.5 kHz)
Region of Interest Builders
triggers
Event Builder
Event Filter
software: full reco.
(200 Hz)
to tape
August 14, 2008
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3. The ATLAS Trigger System
SCT and pixel data
Fast
TracKer
(FTK)
(proposed)
Level One
hardware: calo + muon
(75 kHz)
triggers
triggers
Level Two
software: partial reco.
(3.5 kHz)
tracks
Region of Interest Builders
High Level
Trigger (HLT)
triggers
Event Builder
Event Filter
software: full reco.
(200 Hz)
to tape
August 14, 2008
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4. A Fast Tracker for ATLAS
“Free” tracks at start of Level 2 processing
Tracking exists in L2, but strongly limited by bandwidth
Exacerbated by high-luminosity conditions
FTK frees up CPU time for other tasks or more events
Applications: displaced tracks from b hadrons, tau leptons, track-based isolation for leptons
Ongoing R&D project
Harvard (Franklin, Mills, Morii) joined last summer
Collaborating institutions: Chicago, Frascati, Illinois, Pisa
Cleared for year-long study leading to TDR in March 2009
Timeline: installation in 2012 (LHC  SLHC)
Past year: intensive effort to develop and validate simulation
August 14, 2008
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5. How does FTK work?

6. Simplifed Pattern Recognition
particle track
Group hits into “superhits” (100/ module rather than 100s)
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7. The Associative Memory
Parallel processing
Pre-loaded bank of most probable hit patterns
Dedicated hardware
Look for a match
Like a bingo game:
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8. Linearized Track Finding
Within roads, track-finding problem simplified
Tractable combinatorics
Linear approximations to 2 and track parameter extraction
The Associative Memory associates as set of these linear maps with each pattern
FTK Track finding within road:
Calculate 2 for all permutations of full-resolution hits within road, allowing one layer to have a missing hit
Take hit pattern with best 2, preferentially with no missing layers
Compute track parameters from hit pattern
This step done by DSPs
Output to Level 2 is a list of tracks
August 14, 2008
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9. Forward Tracking Performance

10. Harvard FTK work = 2.5 R (mm) z (mm)
Trigger simulation development effort this year
CM extended the trigger simulation to the disks
Simulation software originally developed for the SVT
CDF geometry is purely cylindrical
Tracking looks for hit on each layer
Extend layers forward using the disks
Ideal is to have one hit per “layer” for each track
Difficulty not from software modification, but description of geometry
= 2.5
R (mm)
z (mm)
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11. FTK Tracking Efficiency
eta
Efficiency is truth tracks matched to FTK reconstructed tracks, divided by all truth tracks
Theoretical maximum to efficiency: fraction of tracks crossing enough layers
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12. Track Parameter Resolution
Impact parameter (d0) resolution not significantly degraded
b hadrons produce tracks with large d0 (> 0.05 cm)
z0 resolution worsens with dip angle but remains good
Compare to size of interaction region: 10 cm (but many interactions…)
track isolation for leptons
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13. Other HLT Work

14. High Level Trigger “Navigation” structure
Event size
(~100kB total)
“Navigation” structure
Information leading to trigger decision
Ideally store for end user analysis, but: > 10 kB/event, where the whole event is 100 kB or smaller)
Task: trim out unneeded objects
Example: group using high-pT leptons does not need jet trigger details
Short-term project, quick payoff, could lead to more work with HLT group
Trigger efficiency measurement
Unified structure to monitor all triggers
Quick turnaround for early data validation
Could develop into working group
(incl. Navigation)
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15. Summary and Outlook Significant contribution to FTK development
Coding and validation of forward tracking in trigger simulation, doubling acceptance
Good tracking efficiency through full pseudorapidity range
Track parameter resolution comparable to central tracks
Cleared for TDR, working toward 2012 installation
Starting up other HLT work
Franklin, Mills, Morii, Smith, potentially more grad students
Potential for real impact on ATLAS performance on a short (~ 1 yr) timescale
Synergy between working knowledge of existing trigger infrastructure and FTK development and integration efforts
August 14, 2008
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16. Backup

17. FTK Architecture RODs Pixels & SCT PIPELINED AM Data Formatter (DF)
EVENT # 1
EVENT # N
50~100 KHz
event rate
HITS
Data
Formatter
(DF)
S-links
SUPER BINS
DATA
ORGANIZER
TRACK FITTER
ROADS
cluster finding
+ split by layer
ROADS + HITS
Raw data
ROBs
Track data
ROB
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18. Global Design Considerations
Bank size for 1/4 of detector
Tradeoffs:
Road size  bank size
big roads = more computation for track finding (time)
narrow roads = bigger pattern banks / AM (cost)
Efficiency
Minimum reconstructable pT (0.5 GeV? 1 GeV?)
10 boards
1 AM board
2 AM boards
August 14, 2008
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